| tags |
|---|
ggg, ggg2024, ggg298 |
All of the lab materials can be found here: https://github.com/ngs-docs/2024-GGG298.
Some suggestions for activities are below - but you can also revisit any of the old labs and ask questions about parts that have you confused!
- Lab 1 - Running RStudio and FastQC
- Lab 2 - Files, directories, and running programs
- Lab 3 - Installing software on remote computers with conda/mamba
- Lab 4 - Markdown, HackMD, and GitHub for note taking
- Lab 5 - Lab miniproject on sourmash
- Lab 6 - Shell scripting, automation, and parallelization
- Lab 7 - Automation, parallelization, and snakemake
- Lab 8 - snakemake and GitHub
- Lab 9 - Quarto & Literate Programming; Slurm and HPC
Get code from Lab 6 - Shell scripting, automation, and parallelization, Lab 7 - Automation, parallelization, and snakemake, and/or Lab 8 - snakemake and GitHub working & push to a new github repository.
- create a new github repo
- clone your repo to farm
- add files to the repo
- make sure they run / work properly
- edit files, update what is on github with the edits
- write a nice README file using Markdown
We didn't get time to do this last week, so work through the tutorial by yourself or in a group!
Interested in using Python on farm with Quarto?
Work through setting up the Python example using a separate kernel in separate conda environment (see tutorial).
Visit the ondemand site for farm with your own account, and experiment with RStudio. You may need to sign up for an account first; you can use datalabgrp as your host.
- start an RStudio server with the defaults;
- set up your own conda environment containing a version of
r-base, and then start a new RStudio session in that conda environment